The relationship between blood alcohol concentration and crash responsibility for fatally injured drivers.

Data for 595 fatally injured drivers in Texas were analyzed using logistic regression to determine the probability of crash responsibility as a function of blood alcohol concentration (BAC). Three independent panelists rated crash responsibility on a three-point scale, based on information contained in traffic accident reports. High inter-rater reliability was noted. Panel members were in agreement 98% of the time, unanimously assigning full responsibility in 61% of the cases and no responsibility in 31% of the cases. In addition to BAC, time of day and day of week were considered as variables in the regression model. A highly significant (P less than .01) relationship was found between BAC and the probability of crash responsibility. Furthermore, results of the analysis support previous studies that noted a high rate of responsibility among fatally injured drivers, in general, even those with negative BAC test results. Such findings are of importance in evaluating driver impairment at various BACs and for determining other factors that interact with alcohol in driver fatality crashes.     

Spatial panel analyses of alcohol outlets and motor vehicle crashes in California: 1999–2008

Although past research has linked alcohol outlet density to higher rates of drinking and many related social problems, there is conflicting evidence of density's association with traffic crashes. An abundance of local alcohol outlets simultaneously encourages drinking and reduces driving distances required to obtain alcohol, leading to an indeterminate expected impact on alcohol-involved crash risk. This study separately investigates the effects of outlet density on (1) the risk of injury crashes relative to population and (2) the likelihood that any given crash is alcohol-involved, as indicated by police reports and single-vehicle nighttime status of crashes. Alcohol outlet density effects are estimated using Bayesian misalignment Poisson analyses of all California ZIP codes over the years 1999–2008. These misalignment models allow panel analysis of ZIP-code data despite frequent redefinition of postal-code boundaries, while also controlling for overdispersion and the effects of spatial autocorrelation. Because models control for overall retail density, estimated alcohol-outlet associations represent the extra effect of retail establishments selling alcohol. The results indicate a number of statistically well-supported associations between retail density and crash behavior, but the implied effects on crash risks are relatively small. Alcohol-serving restaurants have a greater impact on overall crash risks than on the likelihood that those crashes involve alcohol, whereas bars primarily affect the odds that crashes are alcohol-involved. Off-premise outlet density is negatively associated with risks of both crashes and alcohol involvement, while the presence of a tribal casino in a ZIP code is linked to higher odds of police-reported drinking involvement. Alcohol outlets in a given area are found to influence crash risks both locally and in adjacent ZIP codes, and significant spatial autocorrelation also suggests important relationships across geographical units. These results suggest that each type of alcohol outlet can have differing impacts on risks of crashing as well as the alcohol involvement of those crashes.     

The alcohol-related accident risk in Germany: procedure, methods and results

This paper presents the first reliable estimation of the alcohol-related accident risk in Germany by comparing a representative sample of accidents to a representative sample of trips not leading to a crash. The information about the trips was taken from the German Roadside Survey 1992-1994 (n=9087) conducted in Unterfranken, part of Bavaria. These data were weighted according to a representative study of driving in Germany (KONTIV 89). The accident study comprises a representative sample of accidents in Unterfranken in 1993 (n=1968). Relating accident risk to BAC, the global risk function indicates an exponential increase of accident risk for BACs above 0.05%. Controlling for correlating factors leads to an overall lower estimation with, however, the same structure, indicating that alcohol is consumed by drivers in circumstances which further increase the risk introduced by alcohol. Analyzing the attributable risk (AR) shows that about 12% of all accidents are attributable to alcohol. Over 96% of these happen with BACs of 0.05% and above. Thus, measures aimed at reducing the alcohol-related accident risk must focus on larger BACs, especially of 0.08% and above.     

Drug use and the severity of a traffic accident

Several studies have showed that driving under the influence of alcohol and/or certain illicit or medicinal drugs increases the risk of a (severe) crash. Data with respect to the question whether this also leads to a more severe accident are sparse. This study examines the relationship between the use of alcohol, illicit drugs and/or medicinal drugs and the severity of an accident within a group of drivers that were involved in a crash in The Netherlands. Blood samples of 993 drivers, collected in the period from October 1998 through September 1999, were linked to accident characteristics as available from the National Transport Research Centre. The outcome measure was the severity of the accident. An accident was considered severe when the accident had resulted in hospital admission or death. All the blood samples obtained after the accident were screened for the presence of alcohol, illicit drugs (opiates, amphetamines and amphetamine-like substances, cocaine and metabolites, methadone, cannabinoids) and medicinal drugs (benzodiazepines, barbiturates and tricyclic antidepressants). The strength of the associations between exposure to the different classes of alcohol/drugs/medicines and the severity of the accident was evaluated using logistic regression analysis and were expressed as odds ratios (OR), adjusted for age, gender, time of the day, day of the week and urban area. The most frequently detected drugs were cannabinoids, benzodiazepines and cocaine. Our results showed no clear association between the use of alcohol, illicit drug and/or medicinal drug use and the severity of the accident. Given the process of obtaining blood samples from drivers involved in accidents and the retrospective nature of the study, we cannot rule out the occurrence of selection bias. Therefore, our findings need further confirmation.     

Impairment of simulated motorcycle riding performance under low dose alcohol

Crash statistics that include the blood alcohol concentration (BAC) of vehicle operators reveal that crash involved motorcyclists are over represented at low BACs (e.g., ≤0.05%). This riding simulator study compared riding performance and hazard response under three low dose alcohol conditions (sober, 0.02% BAC, 0.05% BAC). Forty participants (20 novice, 20 experienced) completed simulated rides in urban and rural scenarios while responding to a safety-critical peripheral detection task (PDT). Results showed a significant increase in the standard deviation of lateral position in the urban scenario and PDT reaction time in the rural scenario under 0.05% BAC compared with zero alcohol. Participants were most likely to collide with an unexpected pedestrian in the urban scenario at 0.02% BAC, with novice participants at a greater relative risk than experienced riders. Novices chose to ride faster than experienced participants in the rural scenario regardless of BAC. Not all results were significant, emphasising the complex situation of the effects of low dose BAC on riding performance, which needs further research. The results of this simulator study provide some support for a legal BAC for motorcyclists below 0.05%.     

Risk factors for injury accidents among moped and motorcycle riders

Objective

To study and quantify the effect of factors related to the riders of powered two-wheelers on the risk of injury accident involvement.

Methodology

Based on national data held by the police from 1996 to 2005, we conducted a case–control study with responsibility for the accident as the event of interest. We estimated the odds ratios for accident responsibility. Making the hypothesis that the non-responsible riders in the study are representative of all the riders on the road, we thus identified risk factors for being responsible for injury accidents. The studied factors are age, gender, helmet wearing, alcohol consumption, validity of the subject's driving licence and for how long it has been held, the trip purpose and the presence of a passenger on the vehicle. Moped and motorcycle riders are analyzed separately, adjusting for the main characteristics of the accident.

Results

For both moped and motorcycle riders, being male, not wearing a helmet, exceeding the legal limit for alcohol and travelling for leisure purposes increased the risk of accident involvement. The youngest and oldest users had a greater risk of accident involvement. The largest risk factor was alcohol, and we identified a dose–effect relationship between alcohol consumption and accident risk, with an estimated odds ratio of over 10 for motorcycle and moped riders with a BAC of 2 g/l or over. Among motorcycle users, riders without a licence had twice the risk of being involved in an accident than those holding a valid licence. However, the number of years the rider had held a licence reduced the risk of accident involvement. One difference between moped and motorcycle riders involved the presence of a passenger on the vehicle: while carrying a passenger increased the risk of being responsible for the accident among moped riders, it protected against this risk among motorcycle riders.

Conclusion

This analysis of responsibility has identified the major factors contributing to excess risk of injury accidents, some of which could be targeted by prevention programmes.     

Combined effects of alcohol and distraction on driving performance

Although alcohol and distraction are often cited as significant risk factors for traffic crashes, most research has considered them in isolation. It is therefore necessary to consider the interactions between alcohol and distraction impairment sources, especially when examining the relationship between behavior and crash risk. In a driving simulator, the primary goal was to maintain a safe headway to a lead vehicle and the secondary goal was to maintain stable lane position. All participants engaged in distractions that represented different levels of resource competition and half of the participants consumed alcohol (target BAC 0.08 g/dl). Specific comparisons were made between sober driving while distracted and driving intoxicated without distraction. Distraction tasks produced more changes in driving behavior than did alcohol for both longitudinal (primary) and lateral (secondary) driving goals. Alcohol impairment was evident only in relation to lateral driving performance, however there was an amplification of impairment when alcohol and distraction conditions were combined. Distraction resulted in a general level of impairment across all driving goals, whereas participants with alcohol appeared to shed secondary driving goals to “protect” primary driving goals. Drivers’ strategies to cope with alcohol (and distraction) may not be sufficient to offset the increased crash risk.     

Quasi-induced exposure: The choice of exposure metrics

The quasi-induced exposure method is widely used to estimate exposure and risks of different groups of drivers and vehicles. Essentially, this method assumes that non-at-fault or passive parties in two-vehicle collisions represent a random sample of the populations on the road. Most previous works have used the whole sample of collisions to estimate exposure.There has been some concern about possible biases in quasi-induced estimates. In this paper, we argue that (1) biases are mainly due to differences in accident avoidance abilities, speeds and injury risks, and (2) because the influence of these three factors on the probability of being non-at-fault is not the same for every crash type, differences may arise among non-at-fault populations, in which case some crash types would provide a more accurate estimate of exposure than others.We explore the direction of biases due to speed, accident avoidance ability and injury risk in four accident types: accidents between vehicles travelling on different lanes in two-way, two-lane undivided roads; accidents between vehicles travelling on different lanes on multilane roads; intersection accidents; and accidents between vehicles travelling on the same lane. Our analysis shows that more research would be needed concerning the effect of speed on head-on crashes on undivided roads, and crashes on multilane roads.     

Self-reported drug-usage and crash-incidence in breathalyzed drivers

Replies to a question on the medication usage of a large population of drivers subjected to evidential breath analysis were examined, and related to the age, sex and BAC of the driver, and to whether or not he was breath analysed after a crash. In an initial analysis, medications were classified into 13 major groups (including a drug negative, or control, group) and a log-linear analysis carried out on the cross-tabulation of age (five categories) by BAC (five categories) by drug (13 categories) by crash/no crash. (Analysis was restricted to males, since the number of females was very small). A reduced model was obtained, and the ratio of the odds of a crash in each drug group to the odds of a crash in the appropriate drug negative group computed. In a second stage of analysis, the analgesic and CNS depressant categories were expanded to individual agents, and odds ratios again computed. A number of individual drugs and drug groups were associated with an elevated crash risk. These included CNS depressants (diazepam, oxazepam, antidepressants), analgesics (d-propoxyphene) and drugs for the treatment of diabetes. In general, effects were most marked at low BAC's.     

The influence of alcohol, age and number of passengers on the night-time risk of driver fatal injury in New Zealand

Breath alcohol measurements and other data collected at randomly selected roadside sites were combined with data on fatally injured drivers in crashes occurring on the same weekdays and times (Friday and Saturday nights) at locations matched by the size of the nearest town. A logistic model was fitted to these data for the years 1995-2000 to estimate the effects of alcohol, driver's age and the influence of passengers carried on the risk of driver fatal injury in New Zealand. The estimated risks increased steeply with increasing blood alcohol concentration (BAC), closely following an exponential curve at levels below about 200mg/dl (i.e. 0.2%) and increasing less than exponentially thereon. The model fitted to data for drivers under 200mg/dl showed that risks at all BAC levels were statistically significantly higher for drivers aged under 20 (over five times) and for drivers aged 20-29 (three times) than for drivers aged 30 and over. Further, controlling for age and BAC level, driving with a single passenger was associated with approximately half the night-time risk of driver fatal injury relative to driving either solo or with two or more passengers. According to a recent travel survey, the types of passengers carried at the times of night and days of week studied appear to differ significantly from the types of passengers carried generally, which may lead to different passenger effects on driver behaviour. The high relative risk of teenage drivers means that they reach high risk levels commonly regarded as unacceptable in the field of road safety even at their current legal limit of 30mg/dl, particularly when more than one passenger is carried in the car.     

Matched-pair cohort methods in traffic crash research

Standard analysis of matched-pair cohort data requires information only from pairs in which at least one had the study outcome. This can be useful in traffic fatality studies of characteristics that can vary among vehicle occupants, such as seat belt use, as crash databases often lack information about vehicles in which all survived. However, matching crash victims who were in the same vehicle does not necessarily eliminate confounding by vehicle or crash related factors, because the matched occupants must be in different seat positions. This paper reviews three methods for estimating relative risks in matched-pair crash data. The first, Mantel-Haenszel stratified methods, may produce biased estimates if seat position is associated with the outcome. The second, the double-pair comparison method, was designed to deal with confounding by seat position. If the effects of seat position vary according to some vehicle or crash characteristic which is associated with the study exposure, adjustment for this characteristic may be needed to produce unbiased estimates. Third, conditional Poisson regression and Cox proportional hazards regression can produce unbiased estimates, but may require model interaction terms between seat position and vehicle or crash characteristics. This paper reviews some of the strengths and limitations of each of these methods, and illustrates their use in simulated and real crash data.     

Limits of the quasi-induced exposure method when compared with the standard case-control design. Application to the estimation of risks associated with driving under the influence of cannabis or alcohol

The disparities between the quasi-induced exposure (QIE) method and a standard case–control approach with crash responsibility as disease of interest are studied. The 10,748 drivers who had been given compulsory cannabis and alcohol tests subsequent to involvement in a fatal crash in France between 2001 and 2003 were used to compare the two approaches. Odds ratios were assessed using conditional and unconditional logistic regressions. While both approaches found that drivers under the influence of alcohol or cannabis increased the risk of causing a fatal crash, the two approaches are not equivalent. They differ mainly with regards to the driver sample selected. The QIE method results in splitting the overall road safety issue into two sub-studies: a matched case–control study dealing with two-vehicle crashes and a case–control study dealing with single-vehicle crashes but with a specific control group. Using a specific generic term such as “QIE method” should not hide the real underlying epidemiological design. On the contrary, the standard case–control approach studies drivers involved in all type of crashes whatever the distribution of the responsibility in each crash. This method also known as “responsibility analysis” is the most relevant for assessing the overall road safety implications of a driver characteristic.     

Young drivers--reduced crash risk with passengers in the vehicle

Studies have shown that the effect of passengers on accident propensity among young drivers is ambiguous--in some cases positive and some negative. In Sweden, various kinds of information are compiled in registers, including a national accident database and exposure data collected in a national investigation of the driving habits of license holders. Access to such data offers a good opportunity to study crash risks related to driving with and without passengers. This was done for drivers in three different age groups (18-24, 25-64 and >65 years) accompanied by one, two or three or more passengers. Differences in crash risk were estimated using incidence density ratios (IDRs) and 95% confidence intervals. The results show that passengers had an overall protective effect, that is, the crash risk was higher for those who drove alone, regardless of their age or gender. This protective effect increased with every extra passenger (up to eight), indicating that the more passengers in the vehicle, the safer the driving. The influence of passengers was weakest (albeit still positive) among the youngest drivers (ages 18-24 years), especially the males in that group. The protective impact showed the same pattern on all days of the week, but was most marked from Friday to Sunday for most of the drivers, regardless of age.     

The role of the built environment in explaining relationships between perceived and actual pedestrian and bicyclist safety

While the conventional approach to safety planning has emphasized crash analysis with police-reported crash information, transportation professionals increasingly recognize the importance of proactively identifying potential crash risk and considering environmental characteristics. In a proactive approach, individuals’ perception of crash risk provides important information in identifying potential crash risk. As built environment characteristics influence the levels of pedestrian and bicycle safety, this study examined how perceived and actual crash risk are related with each other and with respect to built environmental characteristics. Our results showed that residents who live in low density-single residential neighborhoods are more likely to perceive their neighborhood as dangerous relative to residents of compact, mixed-use neighborhoods even though the latter exhibited higher actual crash rates. The results of path analyses confirmed that a simultaneous but opposite relationship exists between perceived and actual crash risks. Our results indicate that higher actual crash risk increases perceived crash risk, while higher perceived crash risk is negatively associated to actual crash rates. Consequently, low density and non-mixed land uses increase individuals perception of crash risk, and increased perception of risk and unfriendly environment for pedestrian and bikers reduces actual crash rates as a result of behavioral changes. From a policy standpoint, more attention and proactive interventions are desirable in suburban areas beyond the areas with high crash rates, as some of these areas have high-perceived risks.     

Smoking as a risk factor for accident death: a meta-analysis of cohort studies

This meta-analysis discusses the consistency, strength, dose-response, independence, and generalizability of published cohort data on accident death relative risks in smokers. To locate data, three authors independently searched MEDLINE, and bibliographies of the pertinent studies found, for data which allowed estimation of an appropriate cigarette smoker accident death relative risk (and 95% confidence interval). Relative risks and dose-response were summarized by fixed effects and Poisson modeling, respectively. Four pertinent cohort studies including eight populations were located. Cigarette smoking predicted summary accident death relative risks of 1.51 (95% confidence interval 1.27-1.78) versus never smokers and 1.35 (1.17-1.57) versus ex-smokers. Summary dose-response trends were significant (P = 0.0000) versus never or least smoking referents. In individual studies, the smoking/accident death association persisted after adjustment or, in effect stratification, for age, race, sex, and occupation; occupation and time period; or numerous cardiac risk factors. This meta-analysis found significant, consistent, dose-response, often strong and independent (of age, race, and sex), prospective associations of smoking with accident death, internationally. Further studies and warnings of the smoking/accident death associations seem merited.     

The involvement of drugs in drivers of motor vehicles killed in Australian road traffic crashes

A multi-center case-control study was conducted on 3398 fatally-injured drivers to assess the effect of alcohol and drug use on the likelihood of them being culpable. Crashes investigated were from three Australian states (Victoria, New South Wales and Western Australia). The control group of drug- and alcohol-free drivers comprised 50.1% of the study population. A previously validated method of responsibility analysis was used to classify drivers as either culpable or non-culpable. Cases in which the driver "contributed" to the crash (n=188) were excluded. Logistic regression was used to examine the association of key attributes such as age, gender, type of crash and drug use on the likelihood of culpability. Drivers positive to psychotropic drugs were significantly more likely to be culpable than drug-free drivers. Drivers with Delta(9)-tetrahydrocannabinol (THC) in their blood had a significantly higher likelihood of being culpable than drug-free drivers (odds ratio (OR) 2.7, 95% CI 1.02-7.0). For drivers with blood THC concentrations of 5 ng/ml or higher the odds ratio was greater and more statistically significant (OR 6.6, 95% CI 1.5-28.0). The estimated odds ratio is greater than that for drivers with a blood alcohol concentration (BAC) of 0.10-0.15% (OR 3.7, 95% CI 1.5-9.1). A significantly stronger positive association with culpability was seen with drivers positive to THC and with BAC > or =0.05% compared with BAC > or =0.05 alone (OR 2.9, 95% CI 1.1-7.7). Strong associations were also seen for stimulants, particularly in truck drivers. There were non-significant, weakly positive associations of opiates and benzodiazepines with culpability. Drivers positive to any psychoactive drug were significantly more likely to be culpable (OR 1.8, 95% CI 1.3-2.4). Gender differences were not significant, but differences were apparent with age. Drivers showing the highest culpability rates were in the under 25 and over 65 age groups.     

Using the U.S. National Household Travel Survey to estimate the impact of passenger characteristics on young drivers’ relative risk of fatal crash involvement

Motor vehicle crashes are the main cause of morbidity and mortality in teenagers and young adults in the United States. Driving exposure and passenger presence, which can both vary by driver and passenger characteristics, are known to influence crash risk. Some studies have accounted for driving exposure in calculating young driver fatal crash risk in the presence of passengers, but none have estimated crash risk by driver sex and passenger age and sex. One possible reason for this gap is that data collection on driving exposure often precludes appropriate analyses. The purpose of this study was to examine, per 10 million vehicle trips (VT) and vehicle-miles traveled (VMT), the relative risk of fatal crash involvement in 15-20-year-old male and female drivers as a function of their passenger's age and sex, using solo driving as the referent. The Fatality Analysis Reporting System provided fatal motor vehicle crash data from 1999 to 2003 and the 2001 National Household Travel Survey (NHTS) provided VT and VMT. The NHTS collects driving exposure for both household and non-household members (e.g., friends, colleagues), but demographic characteristics only on household members. Missing age and sex of non-household passengers were imputed with hot deck using information from household passengers’ trips with non-household drivers, thereby enabling the calculation of crash rate and relative risk estimates based upon driver and passenger characteristics. Using this approach, the highest risk was found for young male drivers with 16-20-year-old passengers (relative risk [RR] per 10 million VT = 7.99; 95% confidence interval [CI], 7.34-8.69; RR per 10 million VMT = 9.94; 95% CI, 9.13-10.81). Relative risk was also high for 21-34-year-old passengers, again particularly when both drivers and passengers were male. These effects warrant further investigation and underscore the importance of considering driving exposure by passenger characteristics in understanding crash risk. Additionally, as all imputation techniques are imperfect, a more accurate estimation of U.S. fatal crash risk per distance driven would require national surveys to collect data on non-household passenger characteristics.     

Characteristics of rear-end accidents at signalized intersections using multiple logistic regression model

Multi-vehicle rear-end accidents constitute a substantial portion of the accidents occurring at signalized intersections. To examine the accident characteristics, this study utilized the 2001 Florida traffic accident data to investigate the accident propensity for different vehicle roles (striking or struck) that are involved in the accidents and identify the significant risk factors related to the traffic environment, the driver characteristics, and the vehicle types. The Quasi-induced exposure concept and the multiple logistic regression technique are used to perform this analysis. The results showed that seven road environment factors (number of lanes, divided/undivided highway, accident time, road surface condition, highway character, urban/rural, and speed limit), five factors related to striking role (vehicle type, driver age, alcohol/drug use, driver residence, and gender), and four factors related to struck role (vehicle type, driver age, driver residence, and gender) are significantly associated with the risk of rear-end accidents. Furthermore, the logistic regression technique confirmed several significant interaction effects between those risk factors.     

Relative risk of death from ejection by crash type and crash mode

In virtually all circumstances, the chance of survival in a crash is much greater if the occupant is not ejected from the vehicle. Several estimates of the increased risk of death as a result of ejection (ranging from 2.5 to 25) have been made, but none were specific to the crash mode and most did not control for crash severity. The current study examined the relative risk of fatality due to ejection, by crash type and crash mode, using the Fatal Accident Reporting System data from the years 1982 through 1986. Crash type was defined as either single vehicle or multivehicle and crash mode included rollover, nonrollover, and/or direction of impact. Crash severity was controlled for using a paired comparison method of analysis. Both crash type and crash mode were found to have substantial effects on the relative risk of death due to ejection. In addition, risk differences across seating position exist. Depending on crash mode or type, the risks ranged from about 1.5 to 8. Single-vehicle rollover crashes have the highest increased risk of death due to ejection: about eightfold for the driver and sevenfold for the right front passenger.     

Psychoactive substance use and the risk of motor vehicle accidents.

The driving performance is easily impaired as a consequence of the use of alcohol and/or licit and illicit drugs. However, the role of drugs other than alcohol in motor vehicle accidents has not been well established. The objective of this study was to estimate the association between psychoactive drug use and motor vehicle accidents requiring hospitalisation. A prospective observational case-control study was conducted in the Tilburg region of The Netherlands from May 2000 to August 2001. Cases were car or van drivers involved in road crashes needing hospitalisation. Demographic and trauma related data was collected from hospital and ambulance records. Urine and/or blood samples were collected on admission. Controls were drivers recruited at random while driving on public roads. Sampling was conducted by researchers, in close collaboration with the Tilburg police, covering different days of the week and times of the day. Respondents were interviewed and asked for a urine sample. If no urine sample could be collected, a blood sample was requested. All blood and urine samples were tested for alcohol and a number of licit and illicit drugs. The main outcome measures were odds ratios (OR) for injury crash associated with single or multiple use of several drugs by drivers. The risk for road trauma was increased for single use of benzodiazepines (adjusted OR 5.1 (95% Cl: 1.8-14.0)) and alcohol (blood alcohol concentrations of 0.50-0.79 g/l, adjusted OR 5.5 (95% Cl: 1.3-23.2) and >or=0.8 g/l, adjusted OR 15.5 (95% Cl: 7.1-33.9)). High relative risks were estimated for drivers using combinations of drugs (adjusted OR 6.1 (95% Cl: 2.6-14.1)) and those using a combination of drugs and alcohol (OR 112.2 (95% Cl: 14.1-892)). Increased risks, although not statistically significantly, were assessed for drivers using amphetamines, cocaine, or opiates. No increased risk for road trauma was found for drivers exposed to cannabis. The study concludes that drug use, especially alcohol, benzodiazepines and multiple drug use and drug-alcohol combinations, among vehicle drivers increases the risk for a road trauma accident requiring hospitalisation.